Integrated Science Research (ISR)

The ISR program is a phenomenal opportunity for students to try on real science. It gives them the opportunity to experience actual research, all at Blair, while preparing them to continue their endeavors in academic labs at the undergraduate and graduate levels.
Nadia Abascal, PhD, Director of Integrated Science Research

Blair’s Integrated Science Research (ISR) program is a distinctive, two-part research course for highly motivated students eager to engage in authentic scientific inquiry. Beginning with the semester-long Foundations of Integrated Science Research, sophomores and juniors develop the skills and confidence to think and work like scientists—reading professional literature with a critical eye, analyzing current research and mastering the fundamentals of experimental design while exploring a scientific question of personal interest. The course culminates in an original research proposal submitted to the ISR Committee, positioning students to pursue advanced research in their junior and senior years. 

Students continuing into the second year of Integrated Science Research carry out original, student-designed research based on their approved proposals, working with the support of external scientific mentors. Structured as an advanced seminar, these courses offer a high level of independence and intellectual challenge, culminating in a manuscript-style research paper that situates each project within the broader scientific landscape and points toward future avenues of discovery. Together, the ISR program empowers students to pursue ambitious questions, develop advanced research skills and contribute meaningfully to the scientific communities they will enter after Blair.

Recent Student ISR Research Topics

  • AI Detection of Bank Crashes: 

    Using machine learning algorithms to predict bank crashes
     
  • A Comparative Analysis of the RSV Vaccine:

    Using analytical techniques to present the statistical outcomes of infants who received the RSV vaccine in upstate New York
  • Plastic Degradation: UV Light’s Ability to Degrade Plastic:

    Testing a particular UV wavelength’s ability to safely break down petroleum-based polymers
     
  • Building a Biomimetic Mattress:

    Developing code to translate a parent’s breathing and/or heartbeat into the movement of an infant’s bed to mimic the sensations of so-called “co-sleeping”
     
  • The Improvement of Human Safety from Tick-Borne Illness in Sussex & Warren Counties:

    Collecting and analyzing local ticks for patterns of transmittable disease
     

  • Chemically & Virtually Synthesizing Iridescence:

    Virtually simulating iridescence to predict its color and appearance and then testing it in the la

  • Creating a Predictive Algorithm through Machine Learning to Quantify the Possible Invasiveness in a Species:

    Building a model around the invasion of kudzu in the American South to potentially predict other similarly invasive specie

  • Predicting Visual Perception:

    Building a machine learning algorithm to connect visual stimuli to the corresponding fMRI output and thus act as a visual translator for the visually impaire

  • Comparative Analysis of Korean & American Skincare Products:

    Using quantitative measurements of trans-epidermal water loss to test skincare claims at various price points across domestic and international markets

  • The Impact of Color Deficiency on Emotional Processing: 

    Genetically altering zebrafish to be colorblind and testing the psychological impact via behavioral tests

  • Genetically Modifying the P-53 Gene in Drosophila Melanogaster to Test the Effect on Cancer Development and Progression:

    Using CRISPR to study how altering genes linked to tumor growth actually affect disease progression in fruit flies

  • Psychobiotics Mitigating Impulsivity Induced by Artificial Sweeteners & Potential Methods for Application:

    Studying the impact of “healthy” bacterial cultures on fruit flies with artificial-sweetener-induced elevated impulsivity

  • Prediction of Pollution Levels at the Shore:

    Developing a predictive mathematical model to predict optimal times to deploy volunteer groups for beach clean-ups

  • Machine Learning to Detect Skin Cancer & Moles:

    Using an image-detection machine learning algorithm to flag potentially cancerous growths on the skin and writing an accompanying cell phone application to connect patients with medical personnel

  • Optimizing & Exploring Synthetic Spider Silk:

    Using principles of synthetic biology to program E. coli to produce spider silk protein while also testing the most optimal harvesting methods

  • The Impact of Histamine & Antihistamine Treatment on the Gut Microbiome: 

    Using bacterial growth as a readout to see if allergies have impact on the gut microbiom

  • Algorithmic Solution to Housing Disparities in America:

    Writing code to streamline the process by which marginalized populations access subsidized housing

  • Genetic Modification of the MC1R Gene in Drosophila Melanogaster Using CRISPR Technology to Test the Effect of Anesthetics on Drosophila Melanogaster with a Lack of Melanin Production:

    Testing anesthetic tolerance in melanin-deficient fruit flies, rendered as such using CRISPR-based techniques 

  • Optimizing Athletic Performance: Exploring Tendons & Ligaments:

    Using classical engineering testing on synthetic ligaments to develop training regimes that could help prevent ligament and/or tendon injury

  • Hybrid Model Predictive Control Algorithms with Neural Networks for Energy Systems of Buildings & Microgrids:

    Using machine learning algorithms to predictively control energy needs for systems on a power grid or using individually harvested renewable energy